Prof. Dr. Lei Geng | Data Analysis | Best Researcher Award

Prof. Dr. Lei Geng | Data Analysis | Best Researcher Award

Prof. Dr. Lei Geng, Tiangong University, China

Prof. Dr. Lei Geng is a distinguished professor at the School of Life Sciences, Tiangong University, with a focus on computer vision, machine learning, and measurement technology. He received his Ph.D. in 2012 from Tianjin University and has since made significant contributions to the fields of AI, machine vision, and medical technology. With over 80 published papers, Dr. Geng has played a pivotal role in the development of advanced imaging and measurement technologies for industrial and medical applications. His research includes applications in image analysis, 3D dimensional measurement, and hemostatic medical equipment. As a leader in his field, he has led more than 10 national and provincial-level projects and received numerous awards for his technological innovations. 🚀

Professional Profile:

Scopus
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Suitability for the Award

Prof. Dr. Lei Geng is highly suitable for the Best Researcher Award due to his groundbreaking work in AI, machine vision, and medical technology. His research has led to the development of advanced image analysis techniques and high-precision measurement tools, with far-reaching implications for both industrial and healthcare applications. Dr. Geng’s leadership in national and provincial projects, combined with his three provincial-level awards, highlights his ability to drive technological advancements that have a direct impact on society. His contributions to AI-based diagnostics, particularly in otolaryngology, underscore his dedication to improving healthcare through cutting-edge technologies. Prof. Geng’s consistent excellence in research, innovation, and application makes him an ideal candidate for this prestigious award. 🏅

Education

🎓 Dr. Lei Geng earned his Ph.D. in 2012 from Tianjin University, specializing in areas at the intersection of computer vision, machine learning, and measurement technology. His academic journey laid the foundation for his extensive contributions to these fields, including the development of cutting-edge applications in industrial and medical sectors. Dr. Geng’s deep understanding of both theoretical and practical aspects of machine vision and artificial intelligence has made him an expert in creating innovative solutions across multiple industries. His education has fueled his ongoing research and contributions to advancements in AI-driven healthcare and precision measurement technologies. 📘

Experience

🧑‍🏫 Prof. Dr. Lei Geng has extensive teaching and research experience, currently serving as a professor at the School of Life Sciences at Tiangong University. He has been involved in both undergraduate and postgraduate education, teaching courses such as Machine Vision and Deep Learning. Over his career, Dr. Geng has undertaken more than 10 national, provincial, and ministerial-level projects, focusing on industrial and medical applications of machine vision and AI. His experience includes pioneering work in hemostatic medical equipment and high-precision 2D/3D measurement systems. This broad range of expertise positions Dr. Geng as a leader in his field, particularly in the integration of AI technologies with practical, real-world applications. 🌍

Awards and Honors

🏅 Dr. Lei Geng’s excellence in research and technological innovation has been recognized through several prestigious awards. He has received three provincial-level awards, including the Tianjin Second Prize for Technological Invention and the Special Prize of the National Award for Business Science and Technology Progress. These accolades are a testament to his significant contributions to the fields of AI, computer vision, and medical technology. Dr. Geng’s ability to bridge the gap between advanced scientific research and practical applications in industries such as healthcare and manufacturing has made him a highly respected figure in the scientific community. 🌟

Research Focus

🔬 Dr. Lei Geng’s research focuses on four key areas:

  1. Image Analysis & Understanding: Developing AI-based systems for image classification, object detection, and segmentation for industrial and medical applications.
  2. Dimensional Measurement: Applying machine vision and 3D scanning technology for high-precision industrial measurement and target positioning.
  3. Hemostatic Medical Equipment: Innovating in extracorporeal compression and intravascular interventional devices for medical bleeding control.
  4. AI in Otorhinolaryngology: Applying deep learning for disease diagnosis in ear, nose, and throat (ENT) medicine.

His work in these areas aims to integrate AI and machine vision to solve real-world problems, particularly in medical diagnostics and industrial automation. 💡

Publication Top Notes:

  • Direct May Not Be the Best: An Incremental Evolution View of Pose Generation
    • Year: 2024
    • Citations: 1
  • Multi-parametric investigations on the effects of vascular disrupting agents based on a platform of chorioallantoic membrane of chick embryos
    • Year: 2024
  • Label-Aware Dual Graph Neural Networks for Multi-Label Fundus Image Classification
    • Year: 2024
  • Cross-scale contrastive triplet networks for graph representation learning
    • Year: 2024
    • Citations: 4
  • Objective rating method for fabric pilling based on LSNet network
    • Year: 2024
    • Citations: 3

Prof. Dr. Chen-Tung Chen | Performance Analysis | Best Researcher Award

Prof. Dr. Chen-Tung Chen | Performance Analysis | Best Researcher Award

Prof. Dr. Chen-Tung Chen, National United University, Taiwan

Chen-Tung Chen, a renowned academic in Industrial Engineering, holds a distinguished career as a professor at the Department of Information Management, National United University, Taiwan, since 2005. He earned his Bachelor’s and Master’s degrees in Industrial Engineering from National Tsing-Hua University, Taiwan, in 1987. In 1995, he completed his Ph.D. in Industrial Engineering and Management at National Chiao-Tung University, Taiwan. With an extensive academic background, Professor Chen has made significant contributions to various fields, including decision support systems, knowledge management, project management, data mining, and supply chain management. His research integrates fuzzy set theory and multiple criteria decision-making to address complex issues in the aforementioned domains. He has published numerous influential articles in prominent academic journals, shaping the evolution of Industrial Engineering and Information Management in Taiwan and beyond. His work continues to inspire students and professionals alike, making him a key figure in his field.

Professional Profile:

Scopus

Google Scholar

Suitability for Best Researcher Award:

Professor Chen-Tung Chen is highly suitable for the Best Researcher Award due to his remarkable contributions to the fields of Industrial Engineering and Information Management. His work in fuzzy set theory and multiple criteria decision-making has shaped the way complex problems in areas like project management, supply chain management, and knowledge management are approached. Professor Chen’s interdisciplinary expertise, particularly in decision support systems and data mining, has not only advanced academic knowledge but has also driven innovation in practical applications, benefiting both businesses and research communities. His pioneering research and continuous focus on bridging theory with practice demonstrate his leadership and impact in his field.

🎓Education 

Chen-Tung Chen’s academic journey began with a Bachelor’s and Master’s degree in Industrial Engineering from the Department of Industrial Engineering at National Tsing-Hua University, Taiwan, in 1987. Driven by a passion for research and academia, he pursued his Ph.D. in Industrial Engineering and Management at National Chiao-Tung University, Taiwan, which he completed in 1995. His doctoral research further deepened his understanding of decision-making processes and their applications in management systems. This solid educational foundation provided the groundwork for his academic career, allowing him to delve into cutting-edge research areas such as fuzzy set theory, decision support systems, and knowledge management. Throughout his career, Professor Chen has remained committed to the continuous pursuit of knowledge, contributing to advancements in his field. His education, along with his rigorous research and teaching experience, has positioned him as a respected leader in the fields of Industrial Engineering and Information Management.

🏢Experience 

Professor Chen-Tung Chen has had an esteemed career in academia, holding the position of Professor at the Department of Information Management, National United University, Taiwan, since 2005. Prior to this, he earned a solid foundation in Industrial Engineering and Management, where he gained extensive experience in both teaching and research. His early academic journey included earning his Bachelor’s and Master’s degrees in Industrial Engineering from National Tsing-Hua University and his Ph.D. from National Chiao-Tung University, Taiwan. Over the years, Professor Chen has contributed to the growth of his department by offering innovative courses and mentoring numerous graduate students. His interdisciplinary expertise spans several areas, including fuzzy set theory, project management, data mining, and supply chain management. His influence extends beyond the classroom as he has become a key figure in advancing research in decision support systems, knowledge management, and e-business. His vast experience in academia has made him an invaluable resource for students and the research community.

🏅Awards and Honors 

Professor Chen-Tung Chen has been widely recognized for his outstanding contributions to the fields of Industrial Engineering and Information Management. Over the years, he has received several academic accolades for his excellence in research and teaching. As a respected figure in the academic community, he has earned recognition from numerous prestigious journals, where his work has been published. His research, particularly in the application of fuzzy set theory and multiple criteria decision-making, has garnered attention and praise from his peers. Professor Chen’s ability to bridge the gap between theory and practice has led to his involvement in significant projects in the fields of supply chain management, knowledge management, and e-business. His work has had a profound impact on both the academic and professional realms, earning him awards for his contributions to decision support systems and project management. His dedication to advancing his field continues to inspire colleagues, students, and researchers globally.

🔬Research Focus 

Professor Chen-Tung Chen’s research interests are centered on several critical areas in Industrial Engineering and Information Management. His primary focus lies in the application of fuzzy set theory and multiple criteria decision-making techniques to complex decision-making problems in various fields, including project management, supply chain management, and knowledge management. His work in developing decision support systems has led to innovative solutions for optimizing business processes and improving decision-making efficiency. Professor Chen also explores the role of data mining in extracting actionable insights from large datasets, enhancing organizational performance. His research in e-business focuses on improving digital transformation strategies and decision-making processes in modern enterprises. Additionally, his contributions to the design of supply chain management systems aim to create more efficient and responsive global supply networks. Overall, Professor Chen’s research aims to bridge theoretical knowledge with practical applications, providing valuable tools for both academic and professional communities.

Publication Top Notes:

  1. “Extensions of the TOPSIS for group decision-making under fuzzy environment”
    • Citations: 5275
  2. “A fuzzy approach for supplier evaluation and selection in supply chain management”
    • Citations: 2532
  3. “Acute toxicity and biodistribution of different sized titanium dioxide particles in mice after oral administration”
    • Citations: 1526
  4. “Acute toxicological effects of copper nanoparticles in vivo”
    • Citations: 1358
  5. “Diverse applications of nanomedicine”
    • Citations: 1315

 

 

 

 

 

Prof. Gui Gui | Big Data Analysis Awards | Best Scholar Award

Prof. Gui Gui | Big Data Analysis Awards | Best Scholar Award

Prof. Gui Gui, Central South University, China

🎓 Prof. Gui Gui, a distinguished scholar 📚 hailing from Central South University 🇨🇳, boasts a stellar academic journey, culminating in a Ph.D. in Computer Science from the University of Essex 🎓. As a Full Professor at the School of Automation, her expertise in artificial intelligence and big data systems 🤖 propels groundbreaking research, enriching the global academic landscape 🔬. Beyond her role in academia, Gui Gui’s leadership 🌟 and commitment to knowledge dissemination 🌐 shape the future of computer science, inspiring generations of researchers and professionals.

🌐 Professional Profile:

Orcid

🎓 Education

Gui Gui holds a Bachelor of Engineering and a Master of Science in Computer Science from Central South University, Changsha, China. She furthered her education by obtaining a Ph.D. in Computer Science from the University of Essex, Colchester, UK, in 2007, showcasing her commitment to academic excellence and research.

🔬 Research Focus

As a distinguished Full Professor at the School of Automation, Central South University, China, Gui Gui’s research interests revolve around cutting-edge fields such as artificial intelligence, data modeling, and big data systems. Her work contributes significantly to advancing knowledge and innovation in these rapidly evolving domains.

💼 Professional Accomplishments

Gui Gui’s journey in academia has seen her rise to the esteemed position of Full Professor, reflecting her expertise, leadership, and dedication to the field of automation. Her leadership role underscores her influence in shaping the next generation of researchers and professionals in the realm of computer science.

🌐 Contributions & Impact

Gui Gui’s contributions extend beyond the classroom and laboratory, as she actively engages in scholarly activities, collaborations, and knowledge dissemination. Through her research, publications, and academic engagements, she continues to make a profound impact on the global academic community.

Publication Top Notes:

Object detection on low-resolution images with two-stage enhancement
  • Journal: Knowledge-Based Systems
  • Year: 2024-09